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Software Engineer II

Microsoft

Software Engineer II

Microsoft

India, Telangana, Hyderabad

·

On-site

·

Full-time

·

1w ago

Overview

At Microsoft AI, we are redefining what’s possible with data and AI at a global scale. We are seeking an experienced Software Engineer II to architect and build the next generation of big data and AI-driven capabilities.

You will join a true industry-scale data engineering team managing 200 Petabytes of data and 60,000 CPU compute clusters. Our systems form the backbone that powers Bing, MSN, Edge, and Copilot, processing trillions of records to deliver real-time insights, A/B testing, and product decisions to millions of users.

In this role, you will not just write code; you will drive technical strategy. You will modernize our distributed computing infrastructure, integrate AI Coding Agents to revolutionize developer agility, and turn ambiguous problems into reliable, large-scale production systems.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50-mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.

Responsibilities

  • System Design & Architecture: Design, implement, and maintain highly scalable, fault-tolerant distributed data processing systems (batch and streaming).
  • End-to-End Ownership: collaborative ownership of features from technical design and implementation to testing, deployment, and live-site monitoring.
  • Modernization & AI Integration: Integrate AI-driven capabilities into data pipelines to improve efficiency and lead the adoption of AI Coding Agents to accelerate developer velocity and code quality within the team.
  • Operational Excellence: Maintain high service reliability (SLA/SLO). Proactively identify performance bottlenecks, optimize compute costs, and ensure robust monitoring/alerting for a 200PB+ environment.
  • Data Governance: Ensure all architectures comply with strict Security, Privacy, GDPR, and Accessibility standards by design.
  • Collaboration: Partner with Data Scientists, Product Managers, and Principal Engineers to translate ambiguous business requirements into concrete engineering roadmaps.
  • Mentorship: Conduct rigorous code reviews and contribute to the technical growth of junior engineers.

Qualifications Required Qualifications:

  • Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python.
  • OR equivalent experience.
  • 2+ years of professional software development experience with a focus on backend services or data engineering.
  • Coding Proficiency: Proficiency in at least one modern programming language (C#, Java, Scala, Python, or C++) with a solid understanding of object-oriented design and data structures.
  • AI-Assisted Development: Demonstrated experience using AI coding assistants (e.g., GitHub Copilot, Cursor, or custom agents) to rapid-prototype, refactor, and ship production-quality code.
  • DevOps Mindset: Experience with CI/CD pipelines, containerization (Docker/Kubernetes), and infrastructure-as-code.
  • Cloud Native: Deep understanding of cloud ecosystems (Azure, AWS, or GCP), specifically storage (Data Lake/Blob) and compute resources.
  • Growth Mindset: Excellent communication skills with the ability to navigate cross-team dependencies and drive clarity in ambiguous situations.

Preferred Qualifications:

  • Distributed Systems: Hands-on experience with distributed computing frameworks (e.g., Spark, Flink, Hadoop, Kafka, Databricks). Understanding of partitioning, sharding, and consistency models.
  • Big Data Architecture: Experience building Lambda or Kappa architecture for real-time and batch processing.
  • Cost Optimization: Proven track record of optimizing compute/storage resources to reduce operational costs in a high-scale environment.

#MicrosoftAI

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

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关于Microsoft

Microsoft

Microsoft

Public

Microsoft Corporation is an American multinational technology conglomerate headquartered in Redmond, Washington.

10,001+

员工数

Redmond

总部位置

$3000B

企业估值

评价

3.8

5条评价

工作生活平衡

4.1

薪酬

4.3

企业文化

3.4

职业发展

3.2

管理层

3.0

65%

推荐给朋友

优点

Excellent compensation and benefits package

Four-day workweek with improved work-life balance

Supportive managers and teams

缺点

High-pressure environment causing anxiety

Unprofessional interview processes

Limited creative work opportunities

薪资范围

5,620个数据点

Senior/L5

Senior/L5 · Account Management

5份报告

$209,483

年薪总额

基本工资

$181,941

股票

-

奖金

-

$194,895

$209,483

面试经验

1次面试

难度

4.0

/ 5

时长

14-28周

体验

正面 0%

中性 0%

负面 100%

面试流程

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

常见问题

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Culture Fit